Jedat Inc. · TSE:3841

Jedat — Pollen Metrology — Technical Presentation (March 2026)

36 slides from Jedat's technical presentation, Mar 17, 2026

  1. Slide 1: Webinar #5 Build your internal process control software layer in few weeks

    Webinar #5 Build your internal process control software layer in few weeks WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 1 SOFTWARE PLATFORM

  2. Slide 2: Speakers

    Speakers WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 2 SOFTWARE PLATFORM

  3. Slide 3: Webinar #5 – Agenda

    Webinar #5 – Agenda Duration: 45min Build Your Internal Process Control Software Platform in few weeks 30min Introduction to Collaborative AI used in industrial environments Overview of SDK can allow data scientist and process engineer to customize and develop a Software Platform. Full presentation

  4. Slide 4: 1. Context of Data Analytics

    1. Context of Data Analytics WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 4 SOFTWARE PLATFORM

  5. Slide 5: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Simulation R&D and Production line Process Process Process Process parameters modelling t

  6. Slide 6: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Exploding Data Complexity Multiple inspection and metrology tools generating heterogeneou

  7. Slide 7: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Exploding Data Complexity Data Silos Across the Chain Lithography, etch, deposition, bond

  8. Slide 8: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Exploding Data Complexity Data Silos Across the Chain AI Remains Experimental Many pilots

  9. Slide 9: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Exploding Data Complexity Data Silos Across the Chain AI Remains Experimental Engineering

  10. Slide 10: Semiconductor Ecosystem Data Flow

    Semiconductor Ecosystem Data Flow Traditional Engineer-Driven Materials Development From fragmented data to actionable process intelligence Without shared analytics, engineers cannot fully leverage either wheel Exploding Data Complexity Data Silos Across the Chain AI Remains Experimental Engineering

  11. Slide 11: From Bottlenecks to Augmented Engineers

    From Bottlenecks to Augmented Engineers Innovation shouldn’t wait for software Tool/Software Vendor Black Box Fab IT Workflow Bottleneck Pollen Smart3 Augmented Engineer 1. Have an idea 1. Have an idea 1. Have an idea 2. Request new feature 2. Submit a ticket to IT 2. Build your workflow yourself 3.

  12. Slide 12: It needs a Transversal Open Collaborative AI layer

    The industry does not need another AI tool It needs a Transversal Open Collaborative AI layer WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 12 SOFTWARE PLATFORM

  13. Slide 13: 2. Our vision and mission

    2. Our vision and mission WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 13 SOFTWARE PLATFORM

  14. Slide 14: Pollen - Collaborative AI for Process Control

    Pollen - Collaborative AI for Process Control AI-Driven Software for Next-Generation Manufacturing Bridging Data Silos in Material Science with Collaborative AI for Yield Enhancement • Software Company, founded in 2014, • Location: Grenoble – France • Staff Members: 20 (Data Science, Software, Proce

  15. Slide 15: A Transversal Collaborative AI Layer Across the Semiconductor Value Chain

    A Transversal Collaborative AI Layer Across the Semiconductor Value Chain Bridging Metrology, Inspection and Process Intelligence WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 15 SOFTWARE PLATFORM

  16. Slide 16: Augmenting Engineers With a Continuous AI-Driven Development Loop

    Augmenting Engineers With a Continuous AI-Driven Development Loop But maturity does not come from AI alone — it comes from how AI is integrated into engineering loops Simulation R&D and Production line Process Process Experts Process Process parameters modelling DOE tool logfile knowledge Wheel of f

  17. Slide 17: Example - Smart3 Integration for Fabs

    Example 1 - Smart3 Integration for Fabs Use the the SDK & the API WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 17 SOFTWARE PLATFORM

  18. Slide 18: Example - Smart3 Integration for Tool Suppliers

    Example 2 - Smart3 Integration for Tool Suppliers Use the the SDK & the API Production Tool supplier R&D /dev Use cases Model training Algorithm development Tool supplier software platform In- house software Inference Testing Inference CI/CD (model /algorithm Analyzed Data (model /algorithm executio

  19. Slide 19: Build your own process control software in few weeks

    Let’s now apply it to Build your own process control software in few weeks WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 19 SOFTWARE PLATFORM

  20. Slide 20: 3. Industry challenges and proposals for process control software platform

    3. Industry challenges and proposals for the development of process control software platform WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 20 SOFTWARE PLATFORM

  21. Slide 21: Problems to solve

    Problems to solve Focused on the development of a process control software Time-pressure - Long development time - Costly expert time (engineers, data scientists) Data Analysis complexity - Data analysis pipelines are involving various type of data - New processes always require adaptations and cust

  22. Slide 22: Problems to solve

    Problems to solve Focused on the development of a process control software platform Time-pressure - Long development time UI Customization - Costly expert time (engineers, data scientists) Data Analysis complexity - Data analysis pipelines are involving various type of data - New processes always re

  23. Slide 23: From Python Scripts to Software Platform

    From Python Scripts to Software Platform Data Analytics are more accessible than ever: • Process Engineers develop python scripts to automate or improve their analysis • Data Scientists start to be integrated across all type of teams in companies • LLM models allows non expert users to develop their

  24. Slide 24: Customizable User Interface

    Customizable User Interface Example of UI elements to configure algorithms • Names • Type of component • Constraints of values • Layout • Display conditions Define a slider name "Clip max percent" Set its range from 0 to 100 Define the unit (percentage) Define a condition that the slider is visible

  25. Slide 25: Data Management and Visualization

    Data Management and Visualization Data manipulation in a graphical interface is a tedious task • Display (zoom, pixel size management, …) • Figures management (draw, copy/paste, move, export, …) • Label management • Interactions between algorithms and figures • Tables and graphs display Managing het

  26. Slide 26: Workflows

    Workflows Customization and flexibility are key to allow users to develop their own analysis with a no-code approach. • Need to link heterogeneous data together • Assemble various IP to obtain the best of each techniques • Automate workflows to run them on batch of images WEBINAR #5 - BUILD YOUR INT

  27. Slide 27: 4. Use Cases & Demo

    4. Use Cases & Demo WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 27 SOFTWARE PLATFORM

  28. Slide 28: Demo plan

    Demo plan 1. Collaborative Platform ➔ Example of a plugin 2. Plugin creation ➔ More detailed example 3. Workflows with mixed IP 4. Automation WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 28 SOFTWARE PLATFORM

  29. Slide 29: Demo Video – Plugin Manager

    Demo Video – Plugin Manager Create your own Smart3 version WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 29 SOFTWARE PLATFORM

  30. Slide 30: Demo Video – Automatization workflow

    Demo Video – Automatization workflow Application to HVM WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 30 SOFTWARE PLATFORM

  31. Slide 31: Demo Video – Custom Smart3

    Demo Video – Custom Smart3 Application to AFM data WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 31 SOFTWARE PLATFORM

  32. Slide 32: Demo Video – Custom Smart3

    Demo Video – Custom Smart3 Application for optical data for wafer shape application WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 32 SOFTWARE PLATFORM

  33. Slide 33: 5. Next Webinars, Q&A

    5. Next Webinars, Q&A WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 33 SOFTWARE PLATFORM

  34. Slide 34: Webinars in Q1 2026

    Webinars in Q1 2026 Webinar 1 – Dec 2 (2025): Collaborative AI for Next-Gen Semi Manufacturing - A Software Platform Revolution Webinar 2 – Feb 3 (2026): Collaborative AI Software Platform for Metrology Webinar 3: Monday Feb. 16: Collaborative AI for Automatic Defect Classification Webinar 4: Tuesda

  35. Slide 35: Any question?

    Any question? Seminar slides access , please send an email to [email protected] WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 35 SOFTWARE PLATFORM

  36. Slide 36: Thank you

    Thank you WEBINAR #5 - BUILD YOUR INTERNAL PROCESS CONTROL 3/17/2026 36 SOFTWARE PLATFORM

Pollen Metrology — Technical Presentation (March 2026) on 6ix